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HoxBlinc lncRNA reprograms CTCF-independent TADs to drive leukemic transcription and HSC dysregulation in NUP98-rearranged leukemia.
J Clin Invest
January 2025
Division of Pediatric Hematology/Oncology, Department of Pediatrics, Pennsylvania State University College of Medicine, Hershey, United States of America.
Although nucleoporin 98 (NUP98) fusion oncogenes often drive aggressive pediatric leukemia by altering chromatin structure and expression of HOX genes, underlying mechanisms remain elusive. Here, we report that a Hoxb-associated lncRNA HoxBlinc was aberrantly activated in NUP98-PHF23 fusion-driven leukemias. HoxBlinc chromatin occupancies led to elevated MLL1 recruitment and aberrant homeotic topologically associated domains (TADs) that enhanced chromatin accessibilities and activated homeotic/hematopoietic oncogenes.
View Article and Find Full Text PDFAttention-aware differential learning for predicting peptide-MHC class I binding and T cell receptor recognition.
Brief Bioinform
November 2024
School of Computer Science, Northwestern Polytechnical University, Xi'an, 710129 Shaanxi, China.
The identification of neoantigens is crucial for advancing vaccines, diagnostics, and immunotherapies. Despite this importance, a fundamental question remains: how to model the presentation of neoantigens by major histocompatibility complex class I molecules and the recognition of the peptide-MHC-I (pMHC-I) complex by T cell receptors (TCRs). Accurate prediction of pMHC-I binding and TCR recognition remains a significant computational challenge in immunology due to intricate binding motifs and the long-tail distribution of known binding pairs in public databases.
View Article and Find Full Text PDFNovel genetic insight for psoriasis: integrative genome-wide analyses in 863 080 individuals and proteome-wide Mendelian randomization.
Brief Bioinform
November 2024
Department of Dermatology, Daping Hospital, Army Medical University, No. 10, Changjiang Branch Road, Yuzhong District, Chongqing 400042, China.
Psoriasis affects a significant proportion of the worldwide population and causes an extremely heavy psychological and physical burden. The existing therapeutic schemes have many deficiencies such as limited efficacies and various side effects. Therefore, novel ways of treating psoriasis are urgently needed.
View Article and Find Full Text PDFGraph contrastive learning of subcellular-resolution spatial transcriptomics improves cell type annotation and reveals critical molecular pathways.
Brief Bioinform
November 2024
School of Artificial Intelligence, Jilin University, Qianjin Street 2699, 130010 Changchun, China.
Imaging-based spatial transcriptomics (iST), such as MERFISH, CosMx SMI, and Xenium, quantify gene expression level across cells in space, but more importantly, they directly reveal the subcellular distribution of RNA transcripts at the single-molecule resolution. The subcellular localization of RNA molecules plays a crucial role in the compartmentalization-dependent regulation of genes within individual cells. Understanding the intracellular spatial distribution of RNA for a particular cell type thus not only improves the characterization of cell identity but also is of paramount importance in elucidating unique subcellular regulatory mechanisms specific to the cell type.
View Article and Find Full Text PDFA comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions.
Brief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
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